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Optimization & Theory

43,292 papers (3 classified directly here)

Subtopics · a paper can sit in several, so these overlap

Optimization (17,731) Learning Theory (6,809) Bayesian Inference (6,267) Theory (5,579) Statistical Learning (4,564) Neural Network Optimization (4,155) Stochastic Processes (2,948) Stochastic Methods (1,283) Loss Functions (1,220) Distributed Learning (1,202) Online Algorithms (1,013) Statistics (822) Generalization (376) Information Theory (370) Sample Complexity (282) Sparse Optimization (241) Game Theory (151) Convex Optimization (132) Optimal Transport (104) Robust Optimization (84) Distributed Optimization (73) Approximation Algorithms (33)

Papers per year

1
52
352
828
3,646
5,854
2000
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Papers (including subtopics)

An Implicit Form of Krasulina's k-PCA Update without the Orthonormality Constraint AAAI 2020 An Improved Analysis of Stochastic Gradient Descent with Momentum NeurIPS 2020 An Improved Analysis of (Variance-Reduced) Policy Gradient and Natural Policy Gradient Methods NeurIPS 2020 An Information Bottleneck Approach for Controlling Conciseness in Rationale Extraction EMNLP 2020 An information theoretic view on selecting linguistic probes EMNLP 2020 An Interactive Regret-Based Genetic Algorithm for Solving Multi-Objective Combinatorial Optimization Problems AAAI 2020 An Interactive Visualization Platform for Deep Symbolic Regression IJCAI 2020 An Internal Covariate Shift Bounding Algorithm for Deep Neural Networks by Unitizing Layers' Outputs CVPR 2020 An Interpretable and Sample Efficient Deep Kernel for Gaussian Process UAI 2020 An Intrinsically-Motivated Approach for Learning Highly Exploring and Fast Mixing Policies AAAI 2020 An Investigation of the Target Approximation Model for Tone Modeling and Recognition in Continuous Mandarin Speech Interspeech 2020 An Objective for Hierarchical Clustering in Euclidean Space and Its Connection to Bisecting K-means AAAI 2020 A Non-Asymptotic Analysis for Stein Variational Gradient Descent NeurIPS 2020 A nonasymptotic law of iterated logarithm for general M-estimators AISTATS 2020 An Online Learning Framework for Energy-Efficient Navigation of Electric Vehicles IJCAI 2020 A Nonparametric Off-Policy Policy Gradient AISTATS 2020 A Non-Trivial Algorithm Enumerating Relevant Features over Finite Fields ALT 2020 An Optimal Algorithm for Adversarial Bandits with Arbitrary Delays AISTATS 2020 An Optimal Algorithm for Bandit Convex Optimization with Strongly-Convex and Smooth Loss AISTATS 2020 An Optimal Elimination Algorithm for Learning a Best Arm NeurIPS 2020 A Novel Confidence-Based Algorithm for Structured Bandits AISTATS 2020 Ansor: Generating High-Performance Tensor Programs for Deep Learning OSDI 2020 AntMan: Dynamic Scaling on GPU Clusters for Deep Learning OSDI 2020 A Numerical Measure of the Instability of Mapper-Type Algorithms JMLR 2020 An Unbiased Risk Estimator for Learning with Augmented Classes NeurIPS 2020